1. Field of the Invention
The present invention relates to an automated system for managing accounts receivable for outstanding healthcare accounts which preemptively assesses the risk of denials of outstanding healthcare accounts by way of a self-learning engine driven by current data and prioritizes the accounts for follow up according to the risk profile of the account in order to minimize denials by the respective payers and improve the revenue yield while minimizing the revenue cycle.
2. Description of the Prior Art
In general, known medical billing systems, currently being used by healthcare providers, provide statements of current charges for all healthcare services and supplies (collectively “healthcare resources”) to insurance companies, patients and third party payers. In order to facilitate processing of claims for healthcare resources, the American Medical Association (AMA) publishes standardized procedural terminology and associated procedural codes for a myriad of healthcare services including examination, diagnostic, and procedural services. For example, current medical procedure codes are published in “Current Procedural Terminology” 4th edition, published by the AMA, hereby incorporated by reference. The procedural terminology and associated diagnostic codes promulgated by the AMA are the most widely accepted medical nomenclature used to report medical procedures and services under public and private health insurance programs. This procedural terminology is also used for administrative management purposes, such as, claims processing and for developing guidelines for medical care review.
The AMA also publishes codes for medical supplies, also used in processing medical claims. The current codes for medical supplies are published in: “AMA HCPCS 2007 Level II”, published by the AMA, hereby incorporated by reference.
The medical procedure codes greatly streamline the billing process once the codes are entered into the billing records of the patients. In particular, medical procedure codes are manually entered into the patient records for the medical supplies and services provided to the patient by various medical personnel employed by the healthcare provider. On various occasions, incorrect medical billing codes may be recorded in the patient records that are ultimately rejected by the patient's insurance company.
Even though the medical billing codes mentioned above streamline the healthcare billing process, incorrect medical billing codes are sometimes inadvertently included in a patient account. Incorrect billing codes lead to claim denials and thus lost revenue. In addition to lost billing codes, there are a myriad of other reasons for which a medical claim can be denied. One of the more common reasons is that additional documentation is required before the claim can be paid. Many known healthcare accounts receivable management systems initiate follow-up on a claim by claim basis once the claim is denied by the respective payer. Such follow-up requires making a determination of the exact reason for the denial of the claim by the payer and resolving the issue that caused the claim to be denied, if possible. In the cases of claim denials based upon missing documentation, the missing documentation is not normally supplied to the third party payer until after the claim is denied; thereby increasing the revenue cycle, i.e., time from date of discharge of a patient to the date the claim is paid. Due to the volume of accounts receivable that a given healthcare provider has at any given time, manual follow up on each account is virtually impossible.
As such automated systems have been developed. An example of such automated systems for accounts receivable management is disclosed in US Patent Application Publication Nos. US 2008/0208640 A1; US 2008/0103826 A1; and US 2008/0189202 A1, hereby incorporated by reference. Commonly-owned and co-pending U.S. patent application Ser. No. 12/194,721, filed Aug. 20, 2008, entitled “Healthcare Predictive Payment Method” and US Patent US Patent Application Publication Nos. US 2008/0208640 A1 disclose the use of statistical models to predict the patient payment behavior. Such systems are only useful for predicting payment of individual patients. As such, the systems described above are unable to assess the risk of denial of third party healthcare payers, such as insurance companies and Medicare.
US Patent Application Publication No. US 2008/0103826 A1 relates to an automated system for management of health care accounts receivable. In this system, a healthcare provider reports claims level data to a third party “financial intermediary”. The financial intermediary prepares a claim for submittal to a third party payer based upon historical and updated data of the payer, patient and the healthcare provider. Upon approval of the claim form by the healthcare provider, the third party beneficiary submits the claim to the third party payer for payment. Payments less a service fee are credited to the healthcare provider's account. In this system, the administrative overhead associated with healthcare accounts receivable is shifted to a third party, i.e., the financial beneficiary. The system can accelerate payments to the healthcare provider by enabling the healthcare provider to take advantage of the financial intermediary's administrative staff. Even with the assistance of the third party financial intermediary, the system is relatively inefficient since the claims are handled on a claim by claim basis.
US 2008/0189202 A1 discloses a web-based system for collecting overdue health care accounts. The system ranks each overdue account by various factors, such as, (a) outstanding unpaid balance; (b) age of account; (c) prior collection history; (d) demographics of the debtor profile, based on household income and home value; (e) geographic distribution of debtor, based on a parameter which is a member selected from a state and a zip code; (f) type of service provided to the debtor (grouped by DRG codes); (g) date of service provided (grouped in 30 day increments from posting date); and (h) type of debtor/payer classification, the type being a member selected from the group consisting of individual, insurance provider and government provider. The overdue accounts are ranked based on those factors and auctioned for purchase by a third party. Although the system may provide some relief to healthcare providers for overdue accounts, such a system is not useful in accelerating payments to healthcare providers nor in identifying systemic problems in accounts. Also, such a system increases the cost of collection of patient accounts. Moreover, such a system is only useful for predicting payment of individual patients. As such, the system described above is unable to assess the risk of denial of third party healthcare payers, such as insurance companies and Medicare.
Many known health care management systems manage health care accounts receivable by way of the age of the account and the size of the account. With such a system, accounts whose value is greater than a predetermined value are handled prior to lesser value accounts. Unfortunately, there are several problems with such a system. The most significant problem relates to duplication of work. More particularly, in such known systems resolution of the problem leading to the denial of payment are handled on an account by account basis. Thus, in situations in which payment denials are based on the same reason, the resolution of additional claim denials based upon the same reason involved duplication of work by account receivable personnel. For example, if 50 claims from Dr. Smith were denied for knee replacements based upon medical coding errors, each account would be resolved separately, thus involving a significant amount of duplication of work and time.
In order to reduce such duplication of work, automated systems have been developed which detect systemic problems as mentioned above and therefore enable resolution of the claim denial on a batch basis. Examples of such systems are disclosed in various trade articles, such as, “Accounts Receivable Management: Task Management Versus Denial Management”; MedSynergies, Inc., October 2007; and “Securing Revenue with Improved Data Use”; MedAssets, Inc., HFMA Educational Report, hereby incorporated by reference. These articles disclose automated systems for resolving systemic claim denials on a batch basis in order to avoid duplication of work by accounts receivable personnel, as discussed above. However, before a systemic problem can be identified, each claim denial must be analyzed on a claim by claim basis. Even though, these systems are able to utilize data learned through analysis of claim denials to prevent claim denials based on the same reasons, these systems are based strictly on denials. In addition resolution of claim denials with such systems is based on known variables; age of account and amount of claim.
Unfortunately, systems, as described above, are driven by claim denials. In other words, claims have to be denied and the reason or reasons for denial have to be ascertained before resolution of the claim denial can take place. Such systems are known to add 90-120 days to the revenue cycle from the date of discharge. Also, such systems are unable to assess and prioritize the risk of claim denial preemptively to optimize the efforts of healthcare account receivable personnel to improve revenue and decrease the revenue cycle for such healthcare accounts receivable.
Thus, there is a need for an automated accounts receivable management system which reduces the time of the revenue cycle and resolve issues prior to claim denial.